Alcor Labs — Full Stack Engineer

Alcor Labs — Full Stack Engineer

Type: Full-time | On-site | San Francisco, CA Compensation: $180K–$240K base + 0.25–0.75% equity Hiring count: 1 Visa sponsorship: Yes, with limits. Able to support O-1, TN, E-3, H-1B1, H-1B transfers, and H-1B change-of-status for candidates already in the US. No petitions with processing from abroad. F-1 OPT/STEM OPT candidates are fine. Reports to: Elior Benarous, Co-founder

About Alcor Labs

Alcor Labs builds wearable AI co-pilots for industrial field workers, deploying smart glasses powered by agentic vision-language models (VLMs) into legacy industries like data centers, energy grids, and aerospace. The product grounds computer vision and agentic VLMs on bespoke integrations with legacy enterprise systems (Salesforce, ServiceNow, SAP) rather than being another LLM wrapper. Founded by two French co-founders (best friends since age three) with mechanical engineering and AI computer-vision research backgrounds.

Founded: 2026 | Team size: 2 | Total funding: $5M Industry: AI, Hardware, Robotics, Enterprise, Defense, B2B, Manufacturing Website: www.alcor-labs.com Office: San Francisco, CA

Why Candidates Should Join

• Real impact: Agentic VLM smart glasses already deployed at world-leading data center and energy grid customers. Two anchor accounts alone are on path to $10M ARR, with 10-15 more enterprise prospects in pipeline (hyperscalers, top aerospace primes, US Army).
• Differentiated bet: Computer vision and agentic VLM grounded on bespoke integrations with legacy enterprise systems (Salesforce, ServiceNow, SAP). Not another LLM wrapper.
• Strong seed and investors: $5M led by A* with a deep operator network, and Valor as strategic with direct xAI / data center introductions. Founder-led sales already converting.
• Architecture ownership from day one: Define how the product layer scales as customer fleets ramp into the thousands of technicians. Video on wearables is one of the harder versions of full-stack right now (real-time video pipelines, low-latency streaming, mobile + desktop + backend, edge integrations).

Intake Call Summary

• Full Stack Engineer role focuses on scalable system design, apps and platforms optimized for latency; more backend-focused early on with potential for future frontend work.
• Sits alongside two other roles the founders are hiring for (Founding Engineer and AI Engineer); backend-only specialists route to Founding Engineer.
• Ideal Full Stack profile: scalable system design skills, ideally video-heavy experience.
• Comp for Full Stack: $180K–$240K base, 0.25-0.75% equity.
• Work arrangement: on-site role, intense expected hours (founders referenced roughly 70-80 hours/week), with some flexibility for remote on a sixth day.
• Interview process: 15-minute intro call, 45-minute work-experience deep dive, live coding round, then on-site.
• Inconsistency flag: the auto-generated intake transcript refers to the company as "Aqua Labs," while the role page, company section, and website all say "Alcor Labs." Treating Alcor Labs as authoritative.

The Role

A full-stack engineer with 2-5 years of experience who can make scalable architectural decisions and own the product layer around the AI core, comfortable building real-time video pipelines, backend APIs, and mobile/desktop clients for industrial-facing wearable AI products.

What You'll Be Doing

• Ship the end-to-end product experience: smart glasses backend companion app that real customers can use without an engineer present.
• Build and optimize the real-time video/streaming pipeline connecting glasses to the AI core within tight latency budgets.
• Own the backend APIs and data layer the glasses and AI services depend on — reliable, observable, and scalable to early customer load.
• Build the mobile/desktop client for setup, monitoring, and workflow configuration.
• Stand up the deployment and release path so new builds reach hardware in the field safely.
• Define product architecture and engineering practices as the team scales, making smart, scalable decisions early that won't need reworking.
• Be the cross-stack generalist who unblocks the team: debug from frontend through backend to device.

Tech stack: TypeScript, Python, React, React Native, Node.js, AWS, GCP, Supabase, Railway, WebRTC, PostgreSQL, Redis, Docker, real-time streaming, REST APIs, CI/CD

Qualifications

Seniority

• 2-5 years of post-grad SWE experience, ideally early-stage startup exposure. [Required]

Work Experience

• Built and shipped scalable systems zero-to-one with real user traction, owning the whole app end-to-end (backend + APIs + data layer AND the frontend/mobile client a real user touches). Backend-only specialists route to Founding Engineer. [Must have]
• Founding engineer (#1-5) OR early startup experience that shipped OR intense-culture company (Tesla, SpaceX, Anduril, top YC). [Required]
• Big-company tenure (Meta Reality Labs, Snap, Apple Vision, Google, big streaming infra) is a bonus only when on a directly relevant team (AR/smart-glasses, real-time video/streaming, on-device/edge ML) OR paired with a builder signal (founder / early-startup / side projects / OSS). A long single big-tech tenure with no builder signal and no relevant-team work is a negative. [Required]
• Real-time video, streaming, or low-latency pipeline experience (YouTube, Twitch, Cloudflare, Mux). [Strongly preferred]
• Shipped AI pipelines into a product (LLM/agent integration). [Strongly preferred]

Education

• Strong CS/Eng background OR demonstrated equivalent shipping record. [Required]
• Grit proxies: olympiad medals, USACO Platinum, competitive programming rank, or founded-while-studying. [Strongly preferred]

Hard Skills

• Full-stack ability on a modern startup stack (AWS, Supabase, Railway, GCP, etc.). [Must have]
• Frontend / design / UX craft. [Strongly preferred]
• Experience shipping mobile applications (iOS, Android, or strong React Native with native bridges). [Strongly preferred]

Soft Skills

• Makes mature, scalable architectural decisions independently. [Required]

Miscellaneous

• Hacker house (live on site) ideal; minimum on-site 5 days/week in SF. [Must have]

Traits to Avoid

• Legacy/enterprise-only background (Oracle, Infosys, banks).
• Specialist in only one stack layer; no full-stack range.
• Big-tech-only profile with no shipping ownership or side projects.

Role Details

Salary$180K–$240KEquity0.25-0.75%On-site policyOn-site 5 days per week in San Francisco (hacker house / live on site ideal)Visa sponsorshipO-1, TN, E-3, H-1B1, H-1B transfers, and H-1B change-of-status for candidates already in the US. No petitions processed from abroad. F-1 OPT/STEM OPT fine.Employment typeFull-timeLocationSan Francisco, CA

Screening Questions

• Where are you currently based? Would you be able to work on-site 5 days a week in San Francisco? Please specify.
• What visa status do you currently hold? (If non-US)
• What was the hardest thing you've pushed through that no one was making you do? Why did you keep going?
• Which parts of the stack have you personally owned in production: backend, frontend, mobile, infra?
• Something you built end to end and are proud of? What did you get wrong and have to redo?
• Would you be open to living in a hacker house in SF?
• Can you be on-site? If not, are you willing to relocate?
• What is your salary expectation?
• How actively are you exploring new opportunities?

Interview Process

Stage 1 — Submit candidate After submitting, you're notified if the hiring manager wants to proceed.

Stage 2 — Intro Call (15-45 mins) Intro call with Elior. Covers background, motivation, and a deeper dive into past work. Tests for mission alignment (industrial / CV / wearables), AI-pilled curiosity, and intensity match.

Stage 3 — Live Coding Interview (60 mins) Live coding session with the founders. Tests full-stack ability, system design intuition, and how the candidate handles real-time / latency-sensitive scenarios.

Stage 4 — On-site In-person visit to meet the team, see the product, and discuss strategy, GTM, and day-to-day collaboration. Confirms overall cultural fit, ability to contribute to strategy/hiring, and excitement about the mission.

Stage 5 — Offer Extended

Stage 6 — Candidate Hired

Ideal Companies & Backgrounds

Updated Jun 15, 2026

For sourcing reference — these companies and adjacent companies are a starting point.

AR/VR and wearable technology companies Snap Inc., Magic Leap, Squint, nReality, Vuzix Corporation, Niantic

High-intensity hardware/AI companies (Elon-style culture) Cruise, SpaceX, Anduril, Neuralink, xAI, Waymo, Aurora, Cognition, Cursor, Cerebras, Ramp, Greptile, Tesla Motors

Real-time video/streaming infrastructure companies Mux, Daily, Agora, Twitch, Cloudflare, YouTube, Vimeo, LiveKit, Discord, NVIDIA, Netflix

Early-stage YC and seed-stage startups with scrappy engineering teams Glean, Replit, Vercel, Supabase, Retool, Resend, Harvey, Linear

Computer vision and autonomous driving companies Skydio, Waymo, Cruise, Aurora, Nuro, Zoox, Scale AI, Shield AI

Industrial-facing AI/tech companies Palantir Technologies, Samsara, Tulip Interfaces, Augmentir, PTC, Sight Machine, Instrumental Inc., Squint

Ideal Companies Verkada

Non-Ideal Companies (do not source)

Large financial services and banking companies JP Morgan Chase & Co, Goldman Sachs, Capital One, Bank of America, Citigroup, Wells Fargo, Morgan Stanley

Slow-moving corporate behemoths with heavy process cultures Deloitte, KPMG US, EY-Parthenon, PwC, Lockheed Martin, Boeing, General Electric Company

Ideal Candidate Profiles

For reference only — do not source these specific profiles.

Banyar Shin — LinkedIn Software Engineer @ ego (YC W24) | Fremont, United States

• YC company experience with intern to SWE promotion (clear ascending signal)
• Dev tools stack matches early-startup vocabulary (Length, Supabase, etc.)
• Native scrappiness signal from YC environment compensates for fewer years of experience
• Area for improvement: younger end of the 2-5 YOE full-stack range

Rejected Candidate Feedback

• Emphasize candidates with clear zero-to-one ownership — they must show end-to-end product delivery (mobile, backend, real-time video) in an early-stage environment, not just fragmentary experience.
• Prioritize profiles that demonstrate mature scalable architectural decision-making and deep experience with low-latency, real-time pipelines (e.g. video/streaming) relevant to the wearable AI domain.
• Avoid candidates from big tech or legacy industries lacking a builder signal; need those with proven experience in a startup culture with full-stack, agile, hands-on roles.
• Ensure candidates can thrive in the on-site, hacker house environment with high intensity, showing cultural and logistical alignment.